1,720,970 research outputs found
Prediction of Pesticide Interactions with Proteins Involved in Human Reproduction by Using a Virtual Screening Approach: A Case Study of Famoxadone Binding CRBP-III and Izumo
In recent years, the awareness that pesticides can have other effects apart from generic toxicity is growing. In particular, several pieces of evidence highlight their influence on human fertility. In this study, we investigated, by a virtual screening approach, the binding between pesticides and proteins present in human gametes or associated with reproduction, in order to identify new interactions that could affect human fertility. To this aim, we prepared ligand (pesticides) and receptor (proteins) 3D structure datasets from online structural databases (such as PubChem and RCSB), and performed a virtual screening analysis using Autodock Vina. In the comparison of the predicted interactions, we found that famoxadone was predicted to bind Cellular Retinol Binding Protein-III in the retinol-binding site with a better minimum energy value of −10.4 Kcal/mol and an RMSD of 3.77 with respect to retinol (−7.1 Kcal/mol). In addition to a similar network of interactions, famoxadone binding is more stabilized by additional hydrophobic patches including L20, V29, A33, F57, L117, and L118 amino acid residues and hydrogen bonds with Y19 and K40. These results support a possible competitive effect of famoxadone on retinol binding with impacts on the ability of developing the cardiac tissue, in accordance with the literature data on zebrafish embryos. Moreover, famoxadone binds, with a minimum energy value between −8.3 and −8.0 Kcal/mol, to the IZUMO Sperm–Egg Fusion Protein, interacting with a network of polar and hydrophobic amino acid residues in the cavity between the 4HB and Ig-like domains. This binding is more stabilized by a predicted hydrogen bond with the N185 residue of the protein. A hindrance in this position can probably affect the conformational change for JUNO binding, avoiding the gamete membrane fusion to form the zygote. This work opens new interesting perspectives of study on the effects of pesticides on fertility, extending the knowledge to other typologies of interaction which can affect different steps of the reproductive process
Environmental pollution affects the protamine-histone content in human sperm and changes their properties making able to promote DNA oxidative damage: the contribution of molecular investigations
A new biomarker panel of ultraconserved long non-coding RNAs for bladder cancer prognosis by a machine learning based methodology
Background: Recent studies have indicated that a special class of long non-coding RNAs (lncRNAs), namely Transcribed-Ultraconservative Regions are transcribed from specific DNA regions (T-UCRs), 100% conserved in human, mouse, and rat genomes. This is noticeable, as lncRNAs are usually poorly conserved. Despite their peculiarities, T-UCRs remain very understudied in many diseases, including cancer and, yet, it is known that dysregulation of T-UCRs is associated with cancer as well as with human neurological, cardiovascular, and developmental pathologies. We have recently reported the T-UCR uc.8+ as a potential prognostic biomarker in bladder cancer.Results: The aim of this work is to develop a methodology, based on machine learning techniques, for the selection of a predictive signature panel for bladder cancer onset. To this end, we analyzed the expression profiles of T-UCRs from surgically removed normal and bladder cancer tissues, by using custom expression microarray. Bladder tissue samples from 24 bladder cancer patients (12 Low Grade and 12 High Grade), with complete clinical data, and 17 control samples from normal bladder epithelium were analysed. After the selection of preferentially expressed and statistically significant T-UCRs, we adopted an ensemble of statistical and machine learning based approaches (i.e., logistic regression, Random Forest, XGBoost and LASSO) for ranking the most important diagnostic molecules. We identified a signature panel of 13 selected T-UCRs with altered expression profiles in cancer, able to efficiently discriminate between normal and bladder cancer patient samples. Also, using this signature panel, we classified bladder cancer patients in four groups, each characterized by a different survival extent. As expected, the group including only Low Grade bladder cancer patients had greater overall survival than patients with the majority of High Grade bladder cancer. However, a specific signature of deregulated T-UCRs identifies sub-types of bladder cancer patients with different prognosis regardless of the bladder cancer Grade.Conclusions: Here we present the results for the classification of bladder cancer (Low and High Grade) patient samples and normal bladder epithelium controls by using a machine learning application. The T-UCR's panel can be used for learning an eXplainable Artificial Intelligent model and develop a robust decision support system for bladder cancer early diagnosis providing urinary T-UCRs data of new patients. The use of this system instead of the current methodology will result in a non-invasive approach, reducing uncomfortable procedures (such as cystoscopy) for the patients. Overall, these results raise the possibility of new automatic systems, which could help the RNA-based prognosis and/or the cancer therapy in bladder cancer patients, and demonstrate the successful application of Artificial Intelligence to the definition of an independent prognostic biomarker panel
Molecular effects of copper on the reproductive system of mytilus galloprovincialis
This study aims to assess the effects induced by 24 hr exposure to a subtoxic copper concentration on the reproductive system (gonads, spermatozoa, and protamine-like [PL] proteins) of Mytilus galloprovincialis. Inductively coupled plasma-mass spectrometry indicated accumulation of this metal in gonads, spermatozoa, and PL proteins of exposed mussels. Further, real-time polymerase chain reaction analyses showed altered expression levels of mt10 and PL proteins genes in spermatozoa and gonads, respectively, of exposed mussels. Protamine-like proteins, which represent the main basic component of sperm chromatin of this organism, showed a higher DNA binding affinity and a different DNA binding mode in exposed mussels. Moreover, an increased amount of NaCl was required for the release from sperm nuclei of PL-III, the main PL protein component. Finally, PL proteins extracted from exposed mussels promoted DNA oxidative damage in the presence of H 2 O 2. These results demonstrate that the tolerable copper amount could also affect the properties of PL proteins and determine the negative effects on the reproductive system of this organism. These analyses could be useful to develop quick and efficient chromatin-based genotoxicity tests for pollution biomonitoring programs
Structure-function studies on β-glycosidase from Sulfolobus solfataricus. Molecular bases of thermostability
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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